Melbourne Institute of Applied Economic and Social Research - Research Publications
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ItemCompetition, agency and productivity( 2003-07)This paper tests a set of hypotheses relating to agency and Schumpeterian views on how competition affects performance. A survey data set of Australian workplaces is used, with the change in labour productivity growth as the dependent variable. The results show strong support for the idea that intense competition raises productivity growth in managerial workplaces, but not in non-managerial workplaces (i.e. where the principal owner also works). Testing the agency theories in more detail we find no evidence that the number of competitors, the price elasticity of demand or a proxy for bankruptcy (pre-tax losses) are the mechanisms behind the process. For nonmanagerial workplaces the results indicate support for the idea that greater demand uncertainty reduces productivity growth. In contrast, for managerial workplaces greater demand uncertainty tends to raise productivity growth
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ItemFirm performance and investment in R&D and intellectual property( 2002-07)This paper analyses the relationship between innovation - proxied by Research and Development (R&D), patent and trade mark activity - and profitability in a panel of Australian firms (1995 to 1998). Special attention is given to assessing the nature of competitive conditions faced by different firms, as the nature of competition is likely to affect the returns to innovation. The hypothesis is that lower levels of competition will imply higher returns to innovation. To allow for a time lag time before any return to innovation, the market value of the firms is used as a proxy for expected future profits. The results give some support for the main hypothesis: the market's valuation of R&D activity is higher in industries where competition is lower. However, the paper highlights the difficulty in assessing competitive conditions and finds a number of results that challenge the simple hypothesis.
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ItemThe effect of diversification on firm performance(Melbourne Institute of Applied Economic and Social Research, 2001)
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ItemUnderstanding Innovative Firms: An Empirical Analysis of the GAPS( 2000-05)This paper uses data from the Growth and Performance Survey of Australian firms to investigate the determinants of innovation. The measure of innovation is based on whether the firm introduced a new product or process in 1997. Various determinants are investigated including market structure, export status, the use of networks, and training. Regression analysis is conducted separately for manufacturing and non- manufacturing firms, and within each sector by firm size groups. Overall, the results show there is persistence in innovative activities (i.e. firms that innovated in 1995 are more likely to innovation in 1997); small manufacturing firms which use networks tend to be more innovative; and medium sized manufacturing firms that export are also more innovative. However, the main conclusion of the analysis is that many of the explanatory variables are not significant. Moreover, the results vary dramatically across firm size and sector, suggesting that the process of innovation is complex.
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ItemAnalysing Firm-Level Labour Productivity Using Survey Data( 2000-06)This paper investigates the determinants of firm-level labour productivity in the manufacturing sector using GAPS data. These data are from a stratified survey, where the strata are based on industry and firm size. The paper focuses on whether weights should be applied in the regression analysis. Augmented Cobb-Douglas production functions are estimated, where a set of dummies are used as proxies for firm-level knowledge stocks. The regression results show that there are significant differences between the parameters estimated by weighted least squares (WLS) and OLS, particularly for the variables union density and training expenditure. These differences can be caused by parameter heterogeneity (across strata); in theoretical terms this means that applying the same production function across all firms is not appropriate. Given this parameter heterogeneity, both the OLS and WLS methods do not estimate parameters of interest. Instead, there is a requirement to estimate sub-sample regressions. These are presented in the second part of the empirical results.